The Raspberry Pi AI HAT+ is an add-on board with a built-inHailo neural network AI accelerator for Raspberry Pi 5.
It provides an accessible, cost-effective, and power-efficient way to integrate high-performance AI. Explore applications including process control, security, home automation, and robotics with common frameworks such as TensorFlow and PyTorch.
The AI HAT+ is available in 13 and 26 tera-operations per second (TOPS) variants, built around the Hailo-8L and Hailo-8 neural network inference accelerators. It’s suited to everything from entry-level applications to more complex neural processing, with the ability to process multiple concurrent models and AI tasks.
Select the option you require before adding to cart:
The 13 TOPS variant capably runs neural networks for applications including object detection, semantic and instance segmentation, pose estimation, and more.
The 26 TOPS variant can handle larger networks, can run them more quickly, and can more effectively run multiple networks simultaneously.
The AI HAT+ communicates using Raspberry Pi 5’s PCIe Gen 3 interface. When the host Raspberry Pi 5 is running an up-to-date Raspberry Pi OS image, it automatically detects the onboard Hailo accelerator and makes the NPU available for AI computing tasks. The HAT also automatically switches to PCIe Gen 3.0 mode to maximise the full 26 TOPS of compute power available in the Hailo-8 accelerator.
The built-in rpicam-apps camera applications in Raspberry Pi OS natively support the AI module, automatically using the NPU to run compatible post-processing tasks.
Raspberry Pi 5 not included.
Video Example
An example of object detection, pose estimation, and subject segmentation simultaneously on a live camera feed using the 26 TOPS AI HAT+:
Features
Hailo-8 or Hailo-8L accelerator offering 26 TOPS or 13 TOPS inferencing performance respectively
Fully integrated into Raspberry Pi’s camera software stack
Conforms to Raspberry Pi HAT+ specification
Supplied with 16mm stacking header, spacers, and screws to enable fitting on Raspberry Pi 5 with Raspberry Pi Active Cooler in place
Skip to content
